The Value of Information in Automated Sorting: Leveraging Look-Ahead in Multi-Conveyor Systems with Articulated Robotics for Pick and Place

Many production lines utilise conveyor systems with robotic arms for sorting and packing items. The continuously moving conveyor belt requires fast decisions based on the current system state. This study explores the impact of increased information on the performance of a multi conveyor system with strong sequence dependency. Through Implementation of a probabilistic control scheme able to utilise varying degrees of information about future system states, and a continuous time problem formulation, this study evaluates the performance of the real-time scheduling problem solution under different levels of information. Results from extensive testing show that increased future state information asymptotically reduces give-away and improves performance. The findings highlight a relationship between information access and system performance, as well as interactions between different arm coverage configurations. This research provides insights into similar systems and offers a
framework for estimating performance under different constraints and objectives.